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R,SQL, Python, Tableau

San Jose, CA
January 08, 2020

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Manisha Kumari 559-***-**** San Jose, CA - 95136


Graduate Student pursuing Data analytics seeking opportunities as a Data Analyst/Data Scientist.

3 years of Industry experience in Wipro/Microsoft Limited (India) as a Technical Analyst. Innovative and passionate person with expertise in visualization and data analysis. Smart business analytics student with strong proficiency in Python, R, SQL, Excel Solver, Tableau, Power BI and other data analysis tools.


Programming Languages: Python, R, MySQL, NoSQL (Mongo dB), Postgres, SQL, HTML, CSS, NLP

Distributed Systems: Big Data – Hadoop MapReduce, AWS – S3, Pig, Hive

Analytic Methods: R and Python (Regression analysis, Classification, multivariate/logistic regression models, random forest, prediction modeling, neural networks, k-means clustering, decision trees, Text analytics, SVM, PCA), Predictive modeling, Time series Forecasting

Data Visualization: Tableau, Google Analytics, Power BI

Scripting Languages: Python (NumPy, Pandas, Scikit-learn, SciPy, Matplotlib), R (ggmap, maps, ggplot2)

Other Software Tools: SQL Server, Microsoft Office Suite, Advanced Excel, Excel Solver / Precision tree other optimization tools.


Master of Science in Data Analytics, California State Univ East Bay Hayward, Expected Graduation: May 2020, GPA: 3.75

Bachelor of Engineering Electronics, Mumbai Univ, India May 2013 GPA: 3.4


Student Volunteer, California State University - East Bay, 06/2019 – Present

Developing a chatbot using Deep Learning TensorFlow and LSTM (RNN and seq2seq) for college blackboard. Training the bot with (unstructured data) conversation between student and bot and analyzing the result which is giving us 85% accuracy.

Collected the data from mongo DB (conversation between bot and students), performed text analysis in Python to convert unstructured data to structured data.

Developed and presented Tableau dashboards to the university faculty, comparing different parameters to help improve the bot responses. Also working on development of KPI dashboards to monitor bot performance.

Research Assistant, California State University, East Bay, 10/2019 – Present

Developing an automated bot which will automate the login page of CSU East bay portal using python. Creating a rich interface using wxWidgets.

Extracting and analyzing 17,000 student data reports, transforming the data to a suitable template using pandas.

Developing dashboards for university faculty to help them view student progress and different parameters.

Technical Analyst, Wipro- Microsoft, 10/2013 - 12/2016

Assisted in developing the Test Plan, Test Cases and Test Scenarios to be used in testing based on Business Requirements, technical specifications and/or product knowledge.

Troubleshoot and deploy test SharePoint /Project builds to test enhanced BI dashboard, InfoPath form service, task status reporting, site workflows and decision models with project managers to generate higher volume of revenue for clients.

Maintained On-Premises Project 2013, and 2010 infrastructure, as it pertains to server health checks, system background jobs, interfaces with outside agencies and systems, installation of base software, configuration of architectural components, and job management and issue remediation.

Trained and Lead a team of support engineers, responded to their technical questions.

Deployed test SharePoint / Project builds and architectures for testing new services and web parts.

Gather business requirements for system use and reporting.

Develop appropriate views, custom fields, create calendars, and templates to meet the client needs.


Data Scraping ( using different libraries of Python (Pandas, Numpy, xlsxwriter,Matplotlib, Beautiful Soup, URLlib) : Scraped 300 Data science jobs in the USA to understand the most sought skillset and demand for different Data Science job titles using Data Visualization (different libraries), Text mining, NumPy, Pandas, Json, API and HTML tags.

911 Emergency calls analysis (Python): Developed a model for classifying the customers for making 911 calls for reasons such as EMS, fire and traffic. Data used for this model was Emergency 911 calls available on Kaggle. Used pandas to load the dataset. Used different python libraries such as Seaborn, matplotlib, for visualizations. Used heat map and clustering (weekly basis) to see what time period has maximum dialed calls. Analyzed maximum EMS, traffic and fire calls made in day time.

Finding Optimal Decision using Decision tree (Excel/ precision tree): Developed and analyzed to find the optimal solution using Decision tree to help different hotel business management to make an informed decision. Found the solution using EMV criterion, analyzed the optimal decision using Sensitivity Analysis, solver table by varying probabilities.

Customer Churning analysis using Telecom Churning Database (R): Developed a predictive model to recommend a telecom company about how many users are churning based on different parameters. So that they can make use of this analysis for saving customers from churning. Experimental Data used for this model was Customer churning dataset available on Kaggle. Used 3334 customer data along with the time they spent on calls (different period) and different parameters such as different plans they are on. Applied different libraries of R on the data and implemented classification model using logistic Regression, Neural Networks and Classification Tree algorithm. Used different visualizations libraries (ggplot, gplots, data table, heatmaps) to visualize the data and variables contributing for customer churning. Achieved 92% accuracy in classification task.

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